although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. identifying the real time of the process changes is known as change-point estimation problem. there are a number of change point models in the literature however most of the existing approaches are dedicated to normal processes. in this paper we propose a novel appro...

In survival analysis or reliability and maintenance studies, hazard-rate function plays an important role, since it describes the instantaneous failure probability given that the individual survived or the item has not failed up to that instance. Sudden changes in the hazard function may occur due to overhauls, treatment effects or maintenance activities. A problem of statistical interest is th...

the problems of sequential change-point have several important applications in quality control, signal processing, and failure detection in industry and finance. we discuss a bayesian approach in the context of statistical process control: at an unknown time $tau$, the process behavior changes and the distribution of the data changes from p0 to p1. two cases are considered: (i) p0 and p1 are fu...

We consider the testing and estimation of change-points, locations where distribution abruptly changes, in a sequence observations. Motivated by this problem, contribution we first investigate extremes Gaussian fields with trend, which then help us to give asymptotic p-value approximations likelihood ratio statistics from change-point models.

Precise identification of the time when a process has changed enables process engineers to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for a Poisson process in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step < /div> change, a linear trend and a known multip...

In the asymptotic setting of the change-point estimation problem the limiting behavior of Bayes procedures for a general loss function is studied. It is demonstrated that the distribution of the diierence between the Bayes estimator and the parameter converges to the distribution of a (nondegenerate) random variable. The sequence of minimum Bayes risks is shown to converge to its supremum, and ...

Change point detecting problem is an important task in data mining applications. Standard statistical procedures for change point detection, based on maximum likelihood estimators, are complex and require building of parametric models of data. Instead, the methods of computational statistics replace complex statistical procedures with an amount of computation; so these methods become more popul...